5 Keys to Building a Strong Data Structure

June 27, 2022June 30, 2022 Stan

If so, review these areas for optimization

Why is it important?

Let me ask you a question: could you bake a cake without instructions? Sure, but how will it turn out? Will it taste and look good, or will you be left with a pile of globs?

Think about your data structure as the marketing instructions you need to be successful. Creating a data structure enables you to build your marketing strategies and sales initiatives, and ultimately report on your success. A data structure is more about getting the right data (ingredients to your recipe) rather than collecting thousands of data points. Once you have your data structure defined, you can apply meaning to the data you’ve collected. Without any context, it’s just noise.

How do we begin to build a data structure?

Your data structure is the foundation of your marketing day-to-day activities, and it is key to your success. Today, most marketers use data to influence their programs and to build goals that contribute to a company’s bottom line. Have you heard about the data-driven approach or seen it in many, if not all, marketing materials? Building a data structure will allow you to get the insights you need to be agile in an ever-changing digital environment.

Here are 5 key actions to build a strong data structure:

1. Define the data you want to collect

Start with the simple things. Define your Firmographic and Demographic data. Who is the contact/lead, where do they work, what do they do, and where in the buying process are they? Collecting this data information should be inherently part of any marketing or sales process.

Then, think about your business structure. Do you want to categorize your data by region, product, or brand? How will this categorization help you build programs for your business to meet revenue goals? What data is missing and is important to collect? Also, can you get this information directly from your customer, or do you need data augmentation vendors?

If possible, you should always incorporate Behavioral data into your data structure. Such data can be: how a contact/lead is engaging with your website/content/social channels? What are their communication preferences and are you allowed to contact them? Answers to these questions usually reside in your marketing automation tool. Bonus point, most of these tools are automatically collecting this data for you. Your challenge will be how you want to make sense of this data and then connecting it to your funnel for attribution. While this is a good thing to have, it is something that doesn’t have to be incorporated immediately as you build your data structure. If you are just starting off, I would suggest highlighting the areas you think you want to focus on and monitoring these areas independently from your structure. Doing this will allow you to think about the usability of this data and what is really needed to make better business decisions to impact your goals.

Collecting and defining your data structure is not a race; it is a slow and steady marathon to get you to the finish line. You don’t have to have all the pieces defined and ready to go on day one. You can always start with the minimum and then add or iterate as you go.

2. Define your goals

Start with the business objectives, and then figure out how marketing can contribute to these goals. Think of these goals in terms of the funnel (ex: drive awareness, traffic, leads, sales, or customer retention).

What marketing strategies are you implementing to meet those goals? Do these strategies require additional data points for integration? For example, is ABM a play you want to implement? Or, are you doing partner marketing? Is social media a big part of your strategy?

Sometimes, implementing these tactics requires a conversation with your sales or revenue operations team. When building your data structure, think about expanding your list of stakeholders so that you build a comprehensive structure that is supported by different functions in your organization.

3. Define the source and priority of your data

Think about where you want this data to live. Is it your CRM system, your marketing automation tool, or a data warehouse? In actuality, it can be any of these versions or a couple or just one. However, knowing which data resides in which tool is important as you build your data structure. Yes, that’s right we are talking about Data Governance.

While thinking about the data sources, also think about the priority of the data. What is the source of truth for the data you are collecting? Sometimes, different systems are responsible for sources of truth. For example, your CRM can be the source of truth for all account and sales data, while your marketing tool can be the source of truth for your marketing activities and preferences data.

As you build your data structure, identify the sources of truth for each data point so that you know how to prioritize the data when it is integrated between systems. A recent study in the Harvard Business Review found that centralized single sources of truth while it builds standardization sometimes inhibits the ability for you to be flexible in your strategy. Creating flexibility within your data structure allows you to build agile personalized experiences for your marketing strategies. Therefore, you may want to consider different systems that are responsible for different data points as their sources of truth. Ultimately, you can be as complex or as simple as your goals and business strategies require. The main point is to document it so that you and your team can easily identify the priorities and sources of the data.

4. Define your Reporting

Finally, you want to think about how you want to categorize your data. Will you be using custom internal parameters or industry standards like UTM parameters or a combination of these? Building this categorization into your data structure will help you create better reporting and set you on a path for attribution of revenue for all your efforts.

Reporting on your data structure can be complex if you do not follow the steps above. Define, identify, and document all of the data points you are collecting. Also, not every data point will need to be used for reporting purposes. As you build your data structure, identify the data points that will contribute to your reporting and dashboards. For example, you will most likely not report on first name, but you may report on regions and activities (engagements). As you build your data structure, talk to your stakeholders to understand what data is needed to assess your business goals.

Also for reporting, think about how you will govern your data. Is your data clean, and are you getting the right information? Build data completeness reports by volume or data cleansing reports. While this may not contribute to your goals, it improves your personalization and marketing strategies.

5. Affirm the data structure process

Ask yourself and your organization the following questions through every step of the process:

Does this data matter?
Why do I need this data?
Is this data redundant?
Am I aligning this data to goals?

Typically once the data structure is implemented we tend to set and forget. It’s not because we don’t care, but simply because our day-to-day priorities change. Apply a critical filter to the questions above to avoid creating data structures that have no meaning. Let’s not forget the goal of the data structure is to make your efforts easier and to provide quantifiable insights into your efforts.

To easily monitor, build out dashboards that help you answer these questions. Are you collecting the correct data points? Do you have enough volume for the data you are collecting? You can also use qualitative checkpoints with your internal marketing team to see if the data you collected is impacting their goals positively.

No matter what, building a data structure is somewhat fluid. You need to have a lot of the basics in place, but you can always optimize based on learnings or business goals. However, setting up the right process and data structure foundation is important so that you can build upon it.

Final takeaway

To invest in a data-driven marketing approach, you need to have a strong data structure to track the effectiveness of your strategies. You don’t need to perfect it all on day one. The process may be a long-term goal, but you don’t have to delay kicking it off. Once you’ve implemented a data structure, you can begin to see the benefits instead of guessing the effectiveness of your campaigns and targeting. As a result, you can acquire new business by collecting the data you need to ensure you meet your goals. You too can bake like a pro with the right ingredients and recipe. Need help developing your data structure to have more effective marketing? Relationship One is here to help.